Urban habitats and food insecurity

Detalhes bibliográficos
Autor(a) principal: Vaz, Eric
Data de Publicação: 2023
Outros Autores: Damásio, Bruno, Bação, Fernando, Shaker, Richard Ross, Penfound, Elissa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/154833
Resumo: Vaz, E., Damásio, B., Bação, F., Shaker, R. R., & Penfound, E. (2023). Urban habitats and food insecurity: lessons learned throughout a pandemic. Habitat International, 135, 1-11. [102779]. https://doi.org/10.1016/j.habitatint.2023.102779
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spelling Urban habitats and food insecurityLessons learned throughout a pandemicUrban StudiesSDG 2 - Zero HungerSDG 3 - Good Health and Well-beingVaz, E., Damásio, B., Bação, F., Shaker, R. R., & Penfound, E. (2023). Urban habitats and food insecurity: lessons learned throughout a pandemic. Habitat International, 135, 1-11. [102779]. https://doi.org/10.1016/j.habitatint.2023.102779Background An increasing amount of literature raises the issue of food deserts and urban heterogeneity in larger metropolitan cores throughout North America. Specific to Canadian cities, the disparity between access to health, education, and affordable food is of growing concern. Recently, these drivers seem to be significantly linked to the propagation of COVID-19. This paper explores the spatially-explicit dynamics of food deserts in Toronto, by integrating Geographic Information Systems and machine learning to understand the clusters of food deserts. The integration of spatial analysis with self-organizing maps (SOM) offers insights on the relation between neighborhoods, geodemographic profiles and urban characteristics, and whether one might expect consequences of food insecurity given COVID-19. Methods The paper starts out with developing a machine learning algorithm based on SOM to define meaningful clusters within the hedonic dataset. Further to this, an exploratory regression was built per cluster as to allow an exploratory spatial analysis to derive an explanatory framework for the key characteristics of socio-economic profiles within the Greater Toronto Area and impacts of SARS-CoV-2. Results The findings suggest that there are clear spatial profiles within the urban core of Toronto in regards to food deserts, showing a direct relation between socioeconomic characteristics and the results on environmental injustice and livability. These profiles are strongly linked with the areas of COVID-19 occurrence, and share a very similar socio-demographic profile, particularly in regards to young and lower income families. Conclusion There are several food deserts currently in Toronto, Ontario. The integration of policies that involve public health and spatial decision-support, particularly when linked to machine learning to aggregate characteristics of big data, establish a multi-functional understanding of the complexity of food security. This has a direct relation with diet, environment, and the opportunity to enhance subjective well-being in city cores.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNVaz, EricDamásio, BrunoBação, FernandoShaker, Richard RossPenfound, Elissa2023-05-012025-03-28T00:00:00Z2023-05-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article11application/pdfhttp://hdl.handle.net/10362/154833eng0197-3975PURE: 57317631https://doi.org/10.1016/j.habitatint.2023.102779info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:37:17Zoai:run.unl.pt:10362/154833Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:55:46.692769Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Urban habitats and food insecurity
Lessons learned throughout a pandemic
title Urban habitats and food insecurity
spellingShingle Urban habitats and food insecurity
Vaz, Eric
Urban Studies
SDG 2 - Zero Hunger
SDG 3 - Good Health and Well-being
title_short Urban habitats and food insecurity
title_full Urban habitats and food insecurity
title_fullStr Urban habitats and food insecurity
title_full_unstemmed Urban habitats and food insecurity
title_sort Urban habitats and food insecurity
author Vaz, Eric
author_facet Vaz, Eric
Damásio, Bruno
Bação, Fernando
Shaker, Richard Ross
Penfound, Elissa
author_role author
author2 Damásio, Bruno
Bação, Fernando
Shaker, Richard Ross
Penfound, Elissa
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Vaz, Eric
Damásio, Bruno
Bação, Fernando
Shaker, Richard Ross
Penfound, Elissa
dc.subject.por.fl_str_mv Urban Studies
SDG 2 - Zero Hunger
SDG 3 - Good Health and Well-being
topic Urban Studies
SDG 2 - Zero Hunger
SDG 3 - Good Health and Well-being
description Vaz, E., Damásio, B., Bação, F., Shaker, R. R., & Penfound, E. (2023). Urban habitats and food insecurity: lessons learned throughout a pandemic. Habitat International, 135, 1-11. [102779]. https://doi.org/10.1016/j.habitatint.2023.102779
publishDate 2023
dc.date.none.fl_str_mv 2023-05-01
2023-05-01T00:00:00Z
2025-03-28T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/154833
url http://hdl.handle.net/10362/154833
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0197-3975
PURE: 57317631
https://doi.org/10.1016/j.habitatint.2023.102779
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